Faktorértékek

Faktorértékek, often translated as factor values or factor scores, are numerical representations derived from factor analysis. Factor analysis is a statistical technique used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. These factors are theoretical constructs that explain the underlying patterns or relationships among the observed variables.

When factor analysis is performed, the output typically includes factor loadings, which indicate the strength of the relationship between each observed variable and each factor. Factor scores are then calculated for each individual observation in the dataset. These scores represent the estimated value of each factor for that specific observation. Essentially, factor scores are a way to quantify how much of each underlying factor is present in an individual's set of observed variable scores.

The calculation of factor scores usually involves a linear combination of the observed variables, weighted by the factor loadings. Different methods exist for computing factor scores, such as regression factor scoring, Bartlett factor scoring, and Anderson-Rubin factor scoring, each with slightly different statistical properties.

Faktorértékek are useful in several ways. They can be used to reduce the dimensionality of a dataset, allowing for simpler analysis and visualization. They can also serve as new, composite variables that can be used in subsequent statistical analyses, such as regression or cluster analysis, where the original variables might be too numerous or highly correlated. Researchers use faktorértékek to understand individual differences on underlying latent constructs and to summarize complex data into more manageable components.